Developing session-based personalized accommodation recommender system by using LSTM

Name: Developing session-based personalized accommodation recommender system by using LSTM
Author: Can, Y. S., Erkut, H., Giritli, E. B., Kutluay, H., Buyukoguz, K., Demiroğlu, Cenk

İsim	Developing session-based personalized accommodation recommender system by using LSTM
Yazar	Can, Y. S., Erkut, H., Giritli, E. B., Kutluay, H., Buyukoguz, K., Demiroğlu, Cenk
Basım Tarihi:	2022
Basım Yeri	- IEEE
Konu	Hotel recommendation, LSTM, Session-based recommender systems, Tourism
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-166545092-8
Kayıt Numarası	dbd5afb8-8a15-4a33-af69-97f5e0bc859e
Lokasyon	Electrical & Electronics Engineering
Tarih	2022
Örnek Metin	Tourism sector has been transformed by the advances in the Internet technology. Users can search for information and can select their destination from various alternatives by themselves, which brings the need for personal recommender methods. Personalized recommender system development is a complex topic. Demographic information, series of user clicks, and interactions and hotel features are examined to offer the appropriate set of hotels. Since the user interactions, clicks and hotel history is a time series data, Long Short-Term Memory models is a perfect fit to recommend a set of hotels from this data. In this study, we proposed a session-based accommodation recommender system that uses LSTM and achieved promising results.
DOI	10.1109/SIU55565.2022.9864733

Kaynağa git Özyeğin Üniversitesi

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Özyeğin Üniversitesi

Kaynağa git

Developing session-based personalized accommodation recommender system by using LSTM

Yazar Can, Y. S., Erkut, H., Giritli, E. B., Kutluay, H., Buyukoguz, K., Demiroğlu, Cenk

Basım Tarihi 2022

Basım Yeri - IEEE

Konu Hotel recommendation, LSTM, Session-based recommender systems, Tourism

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-166545092-8

Kayıt Numarası dbd5afb8-8a15-4a33-af69-97f5e0bc859e

Lokasyon Electrical & Electronics Engineering

Tarih 2022

Örnek Metin Tourism sector has been transformed by the advances in the Internet technology. Users can search for information and can select their destination from various alternatives by themselves, which brings the need for personal recommender methods. Personalized recommender system development is a complex topic. Demographic information, series of user clicks, and interactions and hotel features are examined to offer the appropriate set of hotels. Since the user interactions, clicks and hotel history is a time series data, Long Short-Term Memory models is a perfect fit to recommend a set of hotels from this data. In this study, we proposed a session-based accommodation recommender system that uses LSTM and achieved promising results.

DOI 10.1109/SIU55565.2022.9864733